25. UAI 2009: Montreal, QC, Canada

• Armen E. Allahverdyan, Aram Galstyan:
  On Maximum a Posteriori Estimation of Hidden Markov Processes. 1-9
  
• Daniel Andrade, Bernhard Sick:
  Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks. 10-18
  
• John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate:
  A Bayesian Sampling Approach to Exploration in Reinforcement Learning. 19-26
  
• Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh:
  On Smoothing and Inference for Topic Models. 27-34
  
• Peter L. Bartlett, Ambuj Tewari:
  REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs. 35-42
  
• Kedar Bellare, Gregory Druck, Andrew McCallum:
  Alternating Projections for Learning with Expectation Constraints. 43-50
  
• Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl:
  Conditional Probability Tree Estimation Analysis and Algorithms. 51-58
  
• Blai Bonet:
  Deterministic POMDPs Revisited. 59-66
  
• Alexandre Bouchard-Côté, Michael I. Jordan:
  Optimization of Structured Mean Field Objectives. 67-74
  
• Jordan L. Boyd-Graber, David M. Blei:
  Multilingual Topic Models for Unaligned Text. 75-82
  
• David M. Bradley, James Bagnell:
  Convex Coding. 83-90
  
• Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman:
  Mean Field Variational Approximation for Continuous-Time Bayesian Networks. 91-100
  
• Vincent Conitzer:
  Prediction Markets, Mechanism Design, and Cooperative Game Theory. 101-108
  
• Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
  L2 Regularization for Learning Kernels. 109-116
  
• Fabio Gagliardi Cozman, Rodrigo Bellizia Polastro:
  Complexity Analysis and Variational Inference for Interpretation-based Probabilistic Description Logic. 117-125
  
• Mark Crowley, John Nelson, David Poole:
  Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making. 126-134
  
• Hal Daumé III:
  Bayesian Multitask Learning with Latent Hierarchies. 135-142
  
• Finale Doshi-Velez, Zoubin Ghahramani:
  Correlated Non-Parametric Latent Feature Models. 143-150
  
• Miroslav Dudík, Geoffrey J. Gordon:
  A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games. 151-160
  
• Yu Fan, Christian R. Shelton:
  Learning Continuous-Time Social Network Dynamics. 161-168
  
• Michael Finegold, Mathias Drton:
  Robust Graphical Modeling with t-Distributions. 169-176
  
• Christian Fritz, Sheila A. McIlraith:
  Generating Optimal Plans in Highly-Dynamic Domains. 177-184
  
• Kuzman Ganchev, Michael Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan:
  Censored Exploration and the Dark Pool Problem. 185-194
  
• Vicenç Gómez, Hilbert J. Kappen, Michael Chertkov:
  Approximate inference on planar graphs using Loop Calculus and Belief Propagation. 195-202
  
• Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron:
  Distributed Parallel Inference on Large Factor Graphs. 203-212
  
• Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík:
  First-Order Mixed Integer Linear Programming. 213-222
  
• Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet:
  New inference strategies for solving Markov Decision Processes using reversible jump MCMC. 223-231
  
• Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn:
  Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. 232-239
  
• Patrik O. Hoyer, Antti Hyttinen:
  Bayesian Discovery of Linear Acyclic Causal Models. 240-248
  
• Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf:
  Identifying confounders using additive noise models. 249-257
  
• Tony Jebara:
  MAP Estimation, Message Passing, and Perfect Graphs. 258-267
  
• Albert Xin Jiang, Kevin Leyton-Brown, Avi Pfeffer:
  Temporal Action-Graph Games: A New Representation for Dynamic Games. 268-276
  
• Kristian Kersting, Babak Ahmadi, Sriraam Natarajan:
  Counting Belief Propagation. 277-284
  
• Oleg Kiselyov, Chung-chieh Shan:
  Monolingual Probabilistic Programming Using Generalized Coroutines. 285-292
  
• Jacek Kisynski, David Poole:
  Constraint Processing in Lifted Probabilistic Inference. 293-302
  
• Samantha Kleinberg, Bud Mishra:
  The Temporal Logic of Causal Structures. 303-312
  
• M. Kumar, Daphne Koller:
  MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts. 313-320
  
• Kenichi Kurihara, Shu Tanaka, Seiji Miyashita:
  Quantum Annealing for Clustering. 321-328
  
• Ping Li:
  Improving Compressed Counting. 329-338
  
• Jun Liu, Shuiwang Ji, Jieping Ye:
  Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. 339-348
  
• Benjamin Lubin, David C. Parkes:
  Quantifying the Strategyproofness of Mechanisms via Metrics on Payoff Distributions. 349-358
  
• Siwei Lyu:
  Interpretation and Generalization of Score Matching. 359-366
  
• Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
  Multiple Source Adaptation and the Rényi Divergence. 367-374
  
• Yi Mao, Guy Lebanon:
  Domain Knowledge Uncertainty and Probabilistic Parameter Constraints. 375-382
  
• Benjamin M. Marlin, Mark W. Schmidt, Kevin P. Murphy:
  Group Sparse Priors for Covariance Estimation. 383-392
  
• Talya Meltzer, Amir Globerson, Yair Weiss:
  Convergent message passing algorithms - a unifying view. 393-401
  
• Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman:
  Convexifying the Bethe Free Energy. 402-410
  
• Thomas P. Minka, Rongjing Xiang, Yuan (Alan) Qi:
  Virtual Vector Machine for Bayesian Online Classification. 411-418
  
• Sara Mostafavi, Quaid Morris:
  Using the Gene Ontology Hierarchy when Predicting Gene Function. 419-427
  
• Mathias Niepert:
  Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence. 428-435
  
• Pekka Parviainen, Mikko Koivisto:
  Exact Structure Discovery in Bayesian Networks with Less Space. 436-443
  
• Kevin Regan, Craig Boutilier:
  Regret-based Reward Elicitation for Markov Decision Processes. 444-451
  
• Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme:
  BPR: Bayesian Personalized Ranking from Implicit Feedback. 452-461
  
• Thomas Richardson:
  A factorization criterion for acyclic directed mixed graphs. 462-470
  
• Daniil Ryabko:
  Characterizing predictable classes of processes. 471-478
  
• Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita:
  Quantum Annealing for Variational Bayes Inference. 479-486
  
• Mark W. Schmidt, Kevin P. Murphy:
  Modeling Discrete Interventional Data using Directed Cyclic Graphical Models. 487-495
  
• Prithviraj Sen, Amol Deshpande, Lise Getoor:
  Bisimulation-based Approximate Lifted Inference. 496-505
  
• Shohei Shimizu, Aapo Hyvärinen, Yoshinobu Kawahara:
  A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model. 506-513
  
• Ilya Shpitser, Judea Pearl:
  Effects of Treatment on the Treated: Identification and Generalization. 514-521
  
• Graham W. Taylor, Geoffrey E. Hinton:
  Products of Hidden Markov Models: It Takes N>1 to Tango. 522-529
  
• Matthias Thimm:
  Measuring Inconsistency in Probabilistic Knowledge Bases. 530-537
  
• Jin Tian, Ru He:
  Computing Posterior Probabilities of Structural Features in Bayesian Networks. 538-547
  
• Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
  Ordinal Boltzmann Machines for Collaborative Filtering. 548-556
  
• Shankar Vembu, Thomas Gärtner, Mario Boley:
  Probabilistic Structured Predictors. 557-564
  
• Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta:
  Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? 565-574
  
• Christopher M. Vigorito:
  Temporal-Difference Networks for Dynamical Systems with Continuous Observations and Actions. 575-582
  
• Yevgeniy Vorobeychik:
  Simulation-Based Game Theoretic Analysis of Keyword Auctions with Low-Dimensional Bidding Strategies. 583-590
  
• Thomas J. Walsh, Istvan Szita, Carlos Diuk, Michael L. Littman:
  Exploring compact reinforcement-learning representations with linear regression. 591-598
  
• Max Welling:
  Herding Dynamic Weights for Partially Observed Random Field Models. 599-606
  
• David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum:
  The Infinite Latent Events Model. 607-614
  
• Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu:
  A Bayesian Framework for Community Detection Integrating Content and Link. 615-622
  
• Jin Yu, S. Vishwanatan, Jian Zhang:
  The Entire Quantile Path of a Risk-Agnostic SVM Classifier. 623-630
  
• Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim:
  Most Relevant Explanation: Properties, Algorithms, and Evaluations. 631-638
  
• Reza Zadeh, Shai Ben-David:
  A Uniqueness Theorem for Clustering. 639-646
  
• Kun Zhang, Aapo Hyvärinen:
  On the Identifiability of the Post-Nonlinear Causal Model. 647-655
  

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